Materials Map

Discover the materials research landscape. Find experts, partners, networks.

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

×

Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Hamer, Mark

  • Google
  • 1
  • 4
  • 131

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2013A non-exercise testing method for estimating cardiorespiratory fitness: Associations with all-cause and cardiovascular mortality in a pooled analysis of eight population-based cohorts131citations

Places of action

Chart of shared publication
Batty, G. David
1 / 1 shared
Odonovan, Gary
1 / 1 shared
Kivimaki, Mika
1 / 2 shared
Stamatakis, Emmanuel
1 / 1 shared
Chart of publication period
2013

Co-Authors (by relevance)

  • Batty, G. David
  • Odonovan, Gary
  • Kivimaki, Mika
  • Stamatakis, Emmanuel
OrganizationsLocationPeople

article

A non-exercise testing method for estimating cardiorespiratory fitness: Associations with all-cause and cardiovascular mortality in a pooled analysis of eight population-based cohorts

  • Batty, G. David
  • Odonovan, Gary
  • Kivimaki, Mika
  • Hamer, Mark
  • Stamatakis, Emmanuel
Abstract

AIMS: <br/><br/>Cardiorespiratory fitness (CRF) is a key predictor of chronic disease, particularly cardiovascular disease (CVD), but its assessment usually requires exercise testing which is impractical and costly in most health-care settings. Non-exercise testing cardiorespiratory fitness (NET-F)-estimating methods are a less resource-demanding alternative, but their predictive capacity for CVD and total mortality has yet to be tested. The objective of this study is to examine the association of a validated NET-F algorithm with all-cause and CVD mortality.<br/><br/>METHODS AND RESULTS: <br/><br/>The participants were 32,319 adults (14,650 men) aged 35-70 years who took part in eight Health Survey for England and Scottish Health Survey studies between 1994 and 2003. Non-exercise testing cardiorespiratory fitness (a metabolic equivalent of VO2max) was calculated using age, sex, body mass index (BMI), resting heart rate, and self-reported physical activity. We followed participants for mortality until 2008. Two thousand one hundred and sixty-five participants died (460 cardiovascular deaths) during a mean 9.0 [standard deviation (SD) = 3.6] year follow-up. After adjusting for potential confounders including diabetes, hypertension, smoking, social class, alcohol, and depression, a higher fitness score according to the NET-F was associated with a lower risk of mortality from all-causes (hazard ratio per SD increase in NET-F 0.85, 95% confidence interval: 0.78-0.93 in men; 0.88, 0.80-0.98 in women) and CVD (men: 0.75, 0.63-0.90; women: 0.73, 0.60-0.92). Non-exercise testing cardiorespiratory fitness had a better discriminative ability than any of its components (CVD mortality c-statistic: NET-F = 0.70-0.74; BMI = 0.45-0.59; physical activity = 0.60-0.64; resting heart rate = 0.57-0.61). The sensitivity of the NET-F algorithm to predict events occurring in the highest risk quintile was better for CVD (0.49 in both sexes) than all-cause mortality (0.44 and 0.40 for men and women, respectively). The specificity for all-cause and CVD mortality ranged between 0.80 and 0.82. The net reclassification improvement of CVD mortality risk (vs. a standardized aggregate score of the modifiable components of NET-F) was 27.2 and 21.0% for men and women, respectively.<br/><br/>CONCLUSION: <br/><br/>The CRF-estimating method NET-F that does not involve exercise testing showed consistent associations with all-cause and cardiovascular mortality, and it had good discrimination and excellent risk reclassification improvement. As such, it merits further attention as a practical and potentially and useful risk prediction tool.<br/>

Topics
  • impedance spectroscopy
  • laser emission spectroscopy
  • alcohol
  • chemical vapor deposition